At least half of the human genome is derived from transposable elements (TEs). These highly repetitive elements often harbor transcription factor binding sites and epigenetic regulatory signals. TEs have shaped gene regulatory networks during evolution and are often dysregulated in diseases. However, the extent to which TEs contribute sequences to functional regulatory networks, and how TE sequences evolved from parasitic DNA to functional elements, remains unclear. Answering these questions will expand our understanding of regulatory networks by including the contributions of TEs to genome-wide patterns of gene regulation. In this proposal, we introduce a novel strategy that combines computational prediction of TE derived cell type-specific enhancers with massively parallel reporter gene assays to understand the impact of TEs to cell type-specific gene regulation. In Specific Aim 1 we plan to develop an epigenomics-based approach to detect TE-derived enhancers and their target genes. We will then test their regulatory activities using CRE-seq, a massive parallel reporter gene assay. We will bring to bear computational models that allow us to predict TE-derived enhancers. If successful, not only will we produce the largest catalog of TE-derived cell type-specific enhancers, but also we will have created a robust framework for detecting the contributions of TEs to gene regulation in any cell type or tissue. In Specific Aim 2 we will develop a phylogenetically informed functional association assay. We will reconstruct sequences representing the evolutionary intermediates of candidate TEs and test the regulatory activities of these sequences with CRE-seq. We will address questions including whether particular classes of TEs gained TF-binding sites and then spread quickly, or whether TEs first spread and later gained TF binding sites. If successful, we will develop an understanding of what sequence features drive the functional potential of TEs, and the modes of evolution followed by different families of TEs during regulatory network evolution. Such an understanding will dramatically improve our picture of gene regulatory network evolution by including the effects of TEs, a major class of fast evolving regulatory sequences that have been largely ignored in functional genomics studies. The methods developed in this proposal will have a high impact on the utility of data produced by consortia such as ENCODE, Roadmap Epigenomics, TCGA, and other large- scale genomics projects, which currently discard most TE derived sequences from their data. Such improvement will in turn accelerate research into understanding the impact of TEs' on normal gene regulation and in human diseases.